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	The package xxl.core.math provides classes that issue mathematical topics. One core competence are
	applications based on nonparametrical statistical methods. This includes particularly
	kernel based estimators. These permit a higher order analysis of given data
	by providing complex statistical estimators, e.g. kernel based density estimators.
	These estimators are applicable for the selectivity estimation of queries and thus 
	cover a main issue of query optimization in database management systems.
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	Since the processing of data streams becomes more important, there are also methods
	provided that build complex statistical estimators online fulfilling the one-pass paradigma
	and consuming constant ressources. Additionally more simple aggregates, that are online computable,
	are available, sometimes even equipped with running confidence intervals.
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	Besides these techniques, there are other mathematical topics adressed. For instance,
	classes realizing numerical integration and the computation of a cubic Bezier-Spline
	interpolate are available and ready-to-use.
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